Search for dissertations about: "data mining distributed"

Showing result 1 - 5 of 19 swedish dissertations containing the words data mining distributed.

2. 1. Data mining of geospatial data: combining visual and automatic methods

   Author : Urška Demšar; Hans Hauska; Peter A. Burrough; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; geographic information science; geoinformatics; geovisualisation; spatial data mining; visual data mining; usability evaluation; Other information technology; Övrig informationsteknik;

   Abstract : Most of the largest databases currently available have a strong geospatial component and contain potentially useful information which might be of value. The discipline concerned with extracting this information and knowledge is data mining. Knowledge discovery is performed by applying automatic algorithms which recognise patterns in the data. READ MORE

4. 2. Clustering Techniques for Mining and Analysis of Evolving Data

   Author : Vishnu Manasa Devagiri; Veselka Boeva; Niklas Lavesson; Sindri Magnússon; Blekinge Tekniska Högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Clustering analysis; Concept drift; Evolutionary clustering; Machine learning; Streaming data; Computer Science; Datavetenskap;

   Abstract : The amount of data generated is on rise due to increased demand for fields like IoT, smart monitoring applications, etc. Data generated through such systems have many distinct characteristics like continuous data generation, evolutionary, multi-source nature, and heterogeneity. READ MORE

5. 3. Efficient Data Streaming Analytic Designs for Parallel and Distributed Processing

   Author : Hannaneh Najdataei; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; stream processing; continuous analysis; scalability; elasticity;

   Abstract : Today, ubiquitously sensing technologies enable inter-connection of physical objects, as part of Internet of Things (IoT), and provide massive amounts of data streams. In such scenarios, the demand for timely analysis has resulted in a shift of data processing paradigms towards continuous, parallel, and multitier computing. READ MORE

6. 4. Mining Big and Fast Data: Algorithms and Optimizations for Real-Time Data Processing

   Author : Muhammad Anis Uddin Nasir; Sarunas Girdzijauskas; Marta Patino-Martinez; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Stream Processing; Load Balancing; Fully Dynamic Graphs; Real-Time Data Processing; Top-k Densest Subgraph; Frequent Subgraph Mining; Informations- och kommunikationsteknik; Information and Communication Technology; Computer Science; Datalogi;

   Abstract : In the last decade, real-time data processing has attracted much attention from both academic community and industry, as the meaning of big data has evolved to incorporate as well the speed of data. The massive and rapid production of data comes via numerous services, i.e., Web, social networks, Internet of Things (IoT) and mobile devices. READ MORE

7. 5. Clustering in the Big Data Era: methods for efficient approximation, distribution, and parallelization

   Author : Amir Keramatian; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Clustering; Approximation-based synopsis; Distributed and Parallel Processing; Applied ML;

   Abstract : Data clustering is an unsupervised machine learning task whose objective is to group together similar items. As a versatile data mining tool, data clustering has numerous applications, such as object detection and localization using data from 3D laser-based sensors, finding popular routes using geolocation data, and finding similar patterns of electricity consumption using smart meters. READ MORE